Summary
In this chapter, you learned why data gravity impedes innovation and how to decompose monolithic databases throughout the phases of the data life cycle. You learned how the CQRS pattern turns the database inside out and ultimately turns the cloud into the database by creating a systemwide transaction log and moving derived data downstream to where it is used. And you learned how to increase team confidence by using materialized views to create inbound bulkheads.
We dug into the details and you learned how to create stream processors that are idempotent and order tolerant, and you saw how to keep data lean. You learned about using the Single Table Design modeling technique to optimize data for performance and how to create stream processors that leverage change data capture to implement the database-first variant of the event sourcing pattern. You also learned about regional data replication, important resource metrics, and redacting sensitive data with envelope encryption...